Identification and control of PMSM using adaptive BP-PID neural network

  • Authors:

  • Chao Cai;Fufei Chu;Zhanshan Wang;Kaili Jia

  • Affiliations:

  • School of Information Science and Engineering, Northeastern University, Liaoning, People's Republic of China;School of Information Science and Engineering, Northeastern University, Liaoning, People's Republic of China;School of Information Science and Engineering, Northeastern University, Liaoning, People's Republic of China;Shandong Liaocheng Power Supply Company, China

  • Venue:
  • ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
  • Year:
  • 2013

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Abstract

The control system of the permanent magnet synchronous motor (PMSM) has the characteristics of nonlinear and strong coupling. Therefore, In order to improve the control precision, the paper presents a novel approach of speed control for PMSM using adaptive BP (back-propagations)-PID neural network. The approach consists of two parts: on-line identification based on BP neural network and the adaptive PID controller. Lyapunov theory is used to prove the stability of the control scheme. Simulation results show that this control method can improve the dynamical performance and enhance the static precision of the speed system.